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This graph maps the connections between all the collaborators of {}'s publications listed on this page.
Each link represents a collaboration on the same publication. The thickness of the link represents the number of collaborations.
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Hold down the "Ctrl" key or the "⌘" key while clicking on the nodes to open the list of this person's publications.
A word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Gagnon, M., Zouaq, A., Aranha, F., Ensan, F., & Jean-Louis, L. (2019). An analysis of the semantic annotation task on the linked data cloud. International Journal of Metadata, Semantics and Ontologies, 13(4), 317-329. External link
Lange Di Cesare, K., Zouaq, A., Gagnon, M., & Jean-Louis, L. (2018). A machine learning filter for the slot filling task. Information, 9(6). Available
Zouaq, A., Gagnon, M., & Jean-Louis, L. (2017). An assessment of open relation extraction systems for the semantic web. Information Systems, 71(Supplement), 228-239. External link
Lange Di Cesare, K., Gagnon, M., Zouaq, A., & Jean-Louis, L. (2016, April). A machine learning filter for relation extraction [Paper]. 25th International World Wide Web Conference (WWW 2016), Montréal, Québec. External link
Jean-Louis, L., Zouaq, A., Gagnon, M., & Ensan, F. (2014, December). An Assessment of Online Semantic Annotators for the Keyword Extraction Task [Paper]. Pacific Rim International Conference on Artificial Intelligence (PRICAI 2014), Gold Coast, Australia. External link
Charton, E., Meurs, M.-J., Jean-Louis, L., & Gagnon, M. (2014, May). Improving entity linking using surface form refinement [Paper]. 9th International Conference on Language Resources and Evaluation (LREC 2014), Reykjavik, Iceland. Unavailable
Charton, É., Meurs, M.-J., Jean-Louis, L., & Gagnon, M. (2014, June). Mutual Disambiguation for Entity Linking [Paper]. 52nd Annual Meeting of the Association for Computational Linguistics, Baltimore, Maryland. External link
Gagnon, M., Zouaq, A., & Jean-Louis, L. (2013, May). Combining Linked-data Semantic Annotators for Extraction of Relevant Expressions [Paper]. 22nd International World Wide Web Conference (WWW 2013), Rio de Janeiro, Brazil. External link
Charton, É., Meurs, M.-J., Jean-Louis, L., & Gagnon, M. (2013). Using collaborative tagging for text classification: from text classification to opinion mining. Informatics, 1(1), 32-51. Available